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A Work/Procrastination Tracker

Hacker News

A Work/Procrastination Tracker

I built this after hearing Tim Urban mention on a podcast with Liv Boeree that he uses a chess clock to track real work vs. procrastination. The idea stuck with me. So I made a very simple web app where you press one button when working and another when you're not. It tracks how much real focus time you’ve done, shows your stats, and reminds you that if you finish 4 hours of real work, the rest of the day is yours. There’s also Pomodoro mode, dark mode, sound notifications, and bilingual support (EN/CZ). It runs in your browser, no login, data is stored locally: https://www.procrastination-slayer.com/ Would love any feedback, especially ideas on how to make it more useful for others struggling with distraction.

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Actual performance

3points
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
75%75% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos
60%60% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
48%48% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
40%40% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
33%33% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
20%20% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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